Many industries employ sophisticated manufacturing equipment that includes multiple sensors and controls, each of which may be carefully monitored during processing to ensure product quality. One method of monitoring the multiple sensors and controls is statistical process monitoring (a means of performing statistical analysis on sensor measurements and process control values (process variables)), which enables automatic detection and/or diagnosis of faults. A “fault” can be a malfunction or maladjustment of manufacturing equipment (e.g., deviation of a machine's operating parameters from intended values), or an indication of a need for preventive maintenance to prevent an imminent malfunction or maladjustment. Faults can produce defects in the devices being manufactured. Accordingly, one goal of statistical process monitoring is to detect and/or diagnose faults before they produce such defects.
One industry approach for statistical process monitoring includes collecting data, acquiring and storing data, analyzing data, and acting. Data is collected by various sensors located on the manufacturing equipment. However, these sensors may not be exposed or accessible. Data is then acquired from the manufacturing equipment and saved or stored in a database that can be located on a server. The data is acquired from various types of manufacturing equipment having different configurations and protocols which slows and complicates the acquisition of the data into the database.
Next, the data is analyzed which requires filtering (e.g., specific runs of semiconductor wafer) and possibly transformations of units. Also, the data must be pre-processed using complex algorithms (e.g., virtual sensors) in order to perform a meaningful analysis. Finally, action must be taken based on the data analysis. For example, faults or errors may indicate a malfunctioning equipment or a need to modified a process parameter immediately on the fly during real-time. The action usually occurs too late because the data analysis requires a significant amount of time. Furthermore, updating or creating new virtual sensors requires restarting or reinstalling the software application being run on a manufacturing machine.